Techniques and Environments for Big Data Analysis: Parallel, Cloud, and Grid Computing
Author:   B. S.P. Mishra ,  Satchidananda Dehuri ,  Euiwhan Kim ,  Gi-Name Wang
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2016
Volume:   17
ISBN:  

9783319275185


Pages:   191
Publication Date:   16 February 2016
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Techniques and Environments for Big Data Analysis: Parallel, Cloud, and Grid Computing


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Overview

This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.

Full Product Details

Author:   B. S.P. Mishra ,  Satchidananda Dehuri ,  Euiwhan Kim ,  Gi-Name Wang
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2016
Volume:   17
Dimensions:   Width: 15.50cm , Height: 1.30cm , Length: 23.50cm
Weight:   4.321kg
ISBN:  

9783319275185


ISBN 10:   3319275186
Pages:   191
Publication Date:   16 February 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction to Big Data Analysis.- Parallel Environments.- A Deep Dive into the Hadoop World to Explore its VariousPerformances.- Natural Language Processing and Machine Learning for Big Data.- Big Data and Cyber Foraging: Future Scope and Challenges.- Parallel GA in Big Data Analysis.- Evolutionary Algorithm Based Techniques to Handle Big Data.- Statistical and Evolutionary Feature Selection TechniquesParallelized using MapReduce Programming Model.- A Data Aware Scheme for Scheduling Big-Data Applications on SAVANNA Hadoop.- The Role of Grid Technologies: A Next Level Combat with Big Data.

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